The Smartphone App Economy and App Ecosystems

This chapter gives an overview of the smartphone app economy and its various constituent ecosystems. It examines the role of the app store model and the proliferation of mobile apps in the shift from value chains controlled by network operators and handset manufacturers, to value networks – or ecosystems – focused around operating systems and apps. It outlines some of the benefits and disadvantages for developers of the app store model for remuneration and distribution. The chapter concludes with a discussion of recent research on the size and employment effects of the app economy.

Using a smartphone application for customer-centric banking

The banking industry is under pressure. In order to compete, banks should adapt to concentrating on the specific customer needs, following an outside-in perspective. This paper presents the design of a business model for banks that considers this development by providing flexible and comprehensive support for retail banking clients. It is demonstrated that the identification of customer processes and the consequent alignment of banking services to those processes implies great potential to increase customer retention in banking. It will be shown that information technology – especially smartphones – can serve as an interface between customer and suppliers to enable an alignment of offerings to customer processes. This approach enables the integration of banks into their customers’ lifestyle, creating emotional value added, improving the personal relationship and the customers’ affiliation with the bank. The paper presents the design of such a customer-process-centric smartphone application and derives success factors for implementation.

Measuring and influencing physical activity with Smartphone technology : a systematic review

Background Rapid developments in technology have encouraged the use of smartphones in physical activity research, although little is known regarding their effectiveness as measurement and intervention tools. Objective This study systematically reviewed evidence on smartphones and their viability for measuring and influencing physical activity. Data Sources Research articles were identified in September 2013 by literature searches in Web of Knowledge, PubMed, PsycINFO, EBSCO, and ScienceDirect. Study Selection The search was restricted using the terms (physical activity OR exercise OR fitness) AND (smartphone* OR mobile phone* OR cell phone*) AND (measurement OR intervention). Reviewed articles were required to be published in international academic peer-reviewed journals, or in full text from international scientific conferences, and focused on measuring physical activity through smartphone processing data and influencing people to be more active through smartphone applications. Study Appraisal and Synthesis Methods Two reviewers independently performed the selection of articles and examined titles and abstracts to exclude those out of scope. Data on study characteristics, technologies used to objectively measure physical activity, strategies applied to influence activity; and the main study findings were extracted and reported. Results A total of 26 articles (with the first published in 2007) met inclusion criteria. All studies were conducted in highly economically advantaged countries; 12 articles focused on special populations (e.g. obese patients). Studies measured physical activity using native mobile features, and/or an external device linked to an application. Measurement accuracy ranged from 52 to 100 % (n = 10 studies). A total of 17 articles implemented and evaluated an intervention. Smartphone strategies to influence physical activity tended to be ad hoc, rather than theory-based approaches; physical activity profiles, goal setting, real-time feedback, social support networking, and online expert consultation were identified as the most useful strategies to encourage physical activity change. Only five studies assessed physical activity intervention effects; all used step counts as the outcome measure. Four studies (three pre–post and one comparative) reported physical activity increases (12–42 participants, 800–1,104 steps/day, 2 weeks–6 months), and one case-control study reported physical activity maintenance (n = 200 participants; >10,000 steps/day) over 3 months. Limitations Smartphone use is a relatively new field of study in physical activity research, and consequently the evidence base is emerging. Conclusions Few studies identified in this review considered the validity of phone-based assessment of physical activity. Those that did report on measurement properties found average-to-excellent levels of accuracy for different behaviors. The range of novel and engaging intervention strategies used by smartphones, and user perceptions on their usefulness and viability, highlights the potential such technology has for physical activity promotion. However, intervention effects reported in the extant literature are modest at best, and future studies need to utilize randomized controlled trial research designs, larger sample sizes, and longer study periods to better explore the physical activity measurement and intervention capabilities of smartphones.

Reliability and criterion-related validity with a smartphone used in timed-up-and-go test

Background The capacity to diagnosys, quantify and evaluate movement beyond the general confines of a clinical environment under effectiveness conditions may alleviate rampant strain on limited, expensive and highly specialized medical resources. An iPhone 4® mounted a three dimensional accelerometer subsystem with highly robust software applications. The present study aimed to evaluate the reliability and concurrent criterion-related validity of the accelerations with an iPhone 4® in an Extended Timed Get Up and Go test. Extended Timed Get Up and Go is a clinical test with that the patient get up from the chair and walking ten meters, turn and coming back to the chair. Methods A repeated measure, cross-sectional, analytical study. Test-retest reliability of the kinematic measurements of the iPhone 4® compared with a standard validated laboratory device. We calculated the Coefficient of Multiple Correlation between the two sensors acceleration signal of each subject, in each sub-stage, in each of the three Extended Timed Get Up and Go test trials. To investigate statistical agreement between the two sensors we used the Bland-Altman method. Results With respect to the analysis of the correlation data in the present work, the Coefficient of Multiple Correlation of the five subjects in their triplicated trials were as follows: in sub-phase Sit to Stand the ranged between r = 0.991 to 0.842; in Gait Go, r = 0.967 to 0.852; in Turn, 0.979 to 0.798; in Gait Come, 0.964 to 0.887; and in Turn to Stand to Sit, 0.992 to 0.877. All the correlations between the sensors were significant (p < 0.001). The Bland-Altman plots obtained showed a solid tendency to stay at close to zero, especially on the y and x-axes, during the five phases of the Extended Timed Get Up and Go test. Conclusions The inertial sensor mounted in the iPhone 4® is sufficiently reliable and accurate to evaluate and identify the kinematic patterns in an Extended Timed Get and Go test. While analysis and interpretation of 3D kinematics data continue to be dauntingly complex, the iPhone 4® makes the task of acquiring the data relatively inexpensive and easy to use.

Mood enhancement using smartphone apps

The significant physical, emotional, educational and social developmental challenges faced by adolescents and young adults are associated with high levels of emotional vulnerability. Thus, the development and use of effective emotion-regulation strategies during this period is critical. Music listening is commonly used by young people to identify, express, enhance and regulate their emotions. Modern mobile technology provides an engaging, easily accessible means of assisting young people with identifying and managing emotions through music. A systematic contextual review of iPhone applications addressing emotions through music was conducted. Their quality was evaluated by two independent raters using the Mobile App Rating Scale (MARS). Three participatory design workshops (PDW; N=13, 6 males, 7 females; age 15-25) were conducted, exploring young people’s use of music to enhance wellbeing. Young people were also asked to trial existing mood and music apps and to conceptualise their ultimate mood-targeting music application. Of the identified 117 music apps, 20 met inclusion criteria (to play songs, not sounds; priced below $5.00). Characteristics and overall quality of the music apps are described and key features of the five highest- rating apps are presented. Thematic analysis of the PDW content identified the following music affect- regulation strategies: relationship building, modifying cognitions, modifying emotions, and immersing in emotions (i.e. habituation or mood enhancement). The application of key learnings from the mobile app review and PDW to the design and development of the new music eScape app will be presented. Implications for future research and for applying the new app in clinical practice are discussed.

Improving adherence physical activity with a smartphone application based on adults with intellectual disabilities (APPCOID)

Background People with intellectual disabilities (ID) have lower levels of physical activity and quality of life and they have a lot of barriers to face when taking part in physical activity. Other problems are the poor adherence to physical activity such people have so this study is designed to improve adherence to physical activity for people with intellectual disabilities with the assistance of an application for smartphones. The aim of the study will be to improve physical activity and physical condition after multimodal intervention and to analyse the promotion of adherence to physical activity through a multimodal intervention and an app intervention (mHealth) in people with ID. Methods A two-stage study will be conducted. In stage 1 a multimodal intervention will take place will be done with physical activity and educational advice over eight weeks, two days a week. Data will be measured after and before the intervention. In stage 2 a randomized controlled trial will be conducted. In the intervention group we will install an application to a smartphone; this application will be a reminder to do a physical activity and they have to select whether they have or haven’t done a physical activity every day. This application will be installed for 18 weeks. Data will be measured after and before the application is installed in two groups. We will measure results 10 weeks later when the two groups don’t have the reminder. The principal outcome used to measure the adherence to physical activity will be the International Physical Activity Questionnaire; secondary outcomes will be a fun-fitness test and self-report survey about quality of life, self-efficacy and social support. Samples will be randomized by sealed envelope in two groups, with approximately 20 subjects in each group. It’s important to know that the therapist will be blinded and won’t know the subjects of each group. Discussion Offering people with ID a multimodal intervention and tool to increase the adherence to a physical activity may increase the levels of physical activity and quality of life. Such a scheme, if beneficial, could be implemented successfully within public health sense. Trial registration ClinicalTrials.gov Identifier: NCT01915381.

Chronic disease risks and use of a smartphone application during a physical activity and dietary intervention in Australian truck drivers

- Objective This study examined chronic disease risks and the use of a smartphone activity tracking application during an intervention in Australian truck drivers (April-October 2014). - Methods Forty-four men (mean age=47.5 [SD 9.8] years) completed baseline health measures, and were subsequently offered access to a free wrist-worn activity tracker and smartphone application (Jawbone UP) to monitor step counts and dietary choices during a 20-week intervention. Chronic disease risks were evaluated against guidelines; weekly step count and dietary logs registered by drivers in the application were analysed to evaluate use of the Jawbone UP. - Results Chronic disease risks were high (e.g. 97% high waist circumference [≥94 cm]). Eighteen drivers (41%) did not start the intervention; smartphone technical barriers were the main reason for drop out. Across 20-weeks, drivers who used the Jawbone UP logged step counts for an average of 6 [SD 1] days/week; mean step counts remained consistent across the intervention (weeks 1–4=8,743[SD 2,867] steps/day; weeks 17–20=8,994[SD 3,478] steps/day). The median number of dietary logs significantly decreased from start (17 [IQR 38] logs/weeks) to end of the intervention (0 [IQR 23] logs/week; p<0.01); the median proportion of healthy diet choices relative to total diet choices logged increased across the intervention (weeks 1–4=38[IQR 21]%; weeks 17–20=58[IQR 18]%). - Conclusions Step counts were more successfully monitored than dietary choices in those drivers who used the Jawbone UP. - Implications Smartphone technology facilitated active living and healthy dietary choices, but also prohibited intervention engagement in a number of these high-risk Australian truck drivers.

Ethnic differences in body composition and anthropometric characteristics in Australian Caucasian and urban Indigenous children

The objective was to compare ethnic differences in anthropometry, including size, proportions and fat distribution, and body composition in a cohort of seventy Caucasian (forty-four boys, twenty-six girls) and seventy-four urban Indigenous (thirty-six boys, thirty-eight girls) children (aged 9–15 years). Anthropometric measures (stature, body mass, eight skinfolds, thirteen girths, six bone lengths and five bone breadths) and body composition assessment using dual-energy X-ray absorptiometry were conducted. Body composition variables including total body fat percentage and percentage abdominal fat were determined and together with anthropometric indices, including BMI (kg/m2), abdominal:height ratio (AHtR) and sum of skinfolds, ethnic differences were compared for each sex. After adjustment for age, Indigenous girls showed significantly (P < 0·05) greater trunk circumferences and proportion of overweight and obesity than their Caucasian counterparts. In addition, Indigenous children had a significantly greater proportion (P < 0·05) of trunk fat. The best model for total and android fat prediction included sum of skinfolds and age in both sexes (>93 % of variation). Ethnicity was only important in girls where abdominal circumference and AHtR were included and Indigenous girls showed significantly (P < 0·05) smaller total/android fat deposition than Caucasian girls at the given abdominal circumference or AHtR values. Differences in anthropometric and fat distribution patterns in Caucasian and Indigenous children may justify the need for more appropriate screening criteria for obesity in Australian children relevant to ethnic origin.

Raman spectroscopic study of the hydroxy-arsenate mineral geminite Cu(AsO3OH)•H2O

The mineral geminite, an hydrated hydroxy-arsenate mineral of formula Cu(AsO3OH)•H2O, has been studied by Raman and infrared spectroscopy. Two minerals from different origins were investigated and the spectra proved quite similar. In the Raman spectra of geminite, four bands are observed at 813, 843, 853 and 885 cm-1. The assignment of these bands is as follows: (a) The band at 853 cm-1 is assigned to the AsO43- ν1 symmetric stretching mode (b) the band at 885 cm-1 is assigned to the AsO3OH2- ν1 symmetric stretching mode (c) the band at 843 cm-1 is assigned to the AsO43- ν3 antisymmetric stretching mode (d) the band at 813 cm-1 is ascribed to the AsO3OH2- ν3 antisymmetric stretching mode. Two Raman bands at 333 and 345 cm-1 are attributed to the ν2 AsO4 3- bending mode and a set of higher wavenumber bands are assigned to the ν4 AsO43- bending mode. A very complex set of overlapping bands is observed in both the Raman and infrared spectra. Raman bands are observed at 2288, 2438, 2814, 3152, 3314, 3448 and 3521 cm-1. Two Raman bands at 2288 and 2438 cm-1 are ascribed to very strongly hydrogen bonded water. The broader Raman bands at 3152 and 3314 cm-1 may be assigned to adsorbed water and not so strongly hydrogen bonded water in the molecular structure of geminate. Two bands at 3448 and 3521 cm-1 are assigned to the OH stretching vibrations of the (AsO3OH)2- units. Raman spectroscopy identified Raman bands attributable to AsO43- and AsO3OH2- units.

A secure framework and related protocols for ubiquitous access to electronic health records using Java sim cards

Ubiquitous access to patient medical records is an important aspect of caring for patient safety. Unavailability of sufficient medical information at the point-ofcare could possibly lead to a fatality. The U.S. Institute of Medicine has reported that between 44,000 and 98,000 people die each year due to medical errors, such as incorrect medication dosages, due to poor legibility in manual records, or delays in consolidating needed information to discern the proper intervention. In this research we propose employing emergent technologies such as Java SIM Cards (JSC), Smart Phones (SP), Next Generation Networks (NGN), Near Field Communications (NFC), Public Key Infrastructure (PKI), and Biometric Identification to develop a secure framework and related protocols for ubiquitous access to Electronic Health Records (EHR). A partial EHR contained within a JSC can be used at the point-of-care in order to help quick diagnosis of a patient’s problems. The full EHR can be accessed from an Electronic Health Records Centre (EHRC) when time and network availability permit. Moreover, this framework and related protocols enable patients to give their explicit consent to a doctor to access their personal medical data, by using their Smart Phone, when the doctor needs to see or update the patient’s medical information during an examination. Also our proposed solution would give the power to patients to modify the Access Control List (ACL) related to their EHRs and view their EHRs through their Smart Phone. Currently, very limited research has been done on using JSCs and similar technologies as a portable repository of EHRs or on the specific security issues that are likely to arise when JSCs are used with ubiquitous access to EHRs. Previous research is concerned with using Medicare cards, a kind of Smart Card, as a repository of medical information at the patient point-of-care. However, this imposes some limitations on the patient’s emergency medical care, including the inability to detect the patient’s location, to call and send information to an emergency room automatically, and to interact with the patient in order to get consent. The aim of our framework and related protocols is to overcome these limitations by taking advantage of the SIM card and the technologies mentioned above. Briefly, our framework and related protocols will offer the full benefits of accessing an up-to-date, precise, and comprehensive medical history of a patient, whilst its mobility will provide ubiquitous access to medical and patient information everywhere it is needed. The objective of our framework and related protocols is to automate interactions between patients, healthcare providers and insurance organisations, increase patient safety, improve quality of care, and reduce the costs.

A secure framework and related protocols for ubiquitous access to electronic health records using Java SIM cards

Ubiquitous access to patient medical records is an important aspect of caring for patient safety. Unavailability of sufficient medical information at the patient point-of-care could possibly lead to a fatality. In this paper we propose employing emergent technologies such as Java SIM Cards (JSC),Smart Phones (SP), Next Generation Networks (NGN), Near Field Communications (NFC), Public Key Infrastructure (PKI), and Biometric Identification to develop a secure framework and related protocols for ubiquitous access to Electronic Health Records (EHRs). A partial EHR contained within a JSC can be used at the patient point-of-care in order to help quick diagnosis of a patient’s problems. The full EHR can be accessed from an Electronic Healthcare Records Centre (EHRC).

Is the iPhone an accurate and useful tool for the monitoring of spinal deformity?

The progression of spinal deformity is traditionally monitored by spinal surgeons using the Cobb method on hardcopy radiographs with a protractor and pencil. The rotation of the spine and ribcage (rib hump) in scoliosis is measured with a simple hand-held inclinometer (Scoliometer). The iPhone and other smart phones have the capability to accurately sense inclination, and can therefore be used to measure Cobb angles and rib hump angulation. The purpose of this study was to quantify the performance of the iPhone compared to a standard protractor for measuring Cobb angles and the Scoliometer for measuring rib humps. The study concluded that the iPhone is a clinically equivalent measuring tool to the traditional protractor and Scoliometer

Use of the iPhone for Cobb angle measurement in scoliosis

Purpose: The Cobb technique is the universally accepted method for measuring the severity of spinal deformities. Traditionally, Cobb angles have been measured using protractor and pencil on hardcopy radiographic films. The new generation of mobile phones make accurate angle measurement possible using an integrated accelerometer, providing a potentially useful clinical tool for assessing Cobb angles. The purpose of this study was to compare Cobb angle measurements performed using an Apple iPhone and traditional protractor in a series of twenty Adolescent Idiopathic Scoliosis patients. Methods: Seven observers measured major Cobb angles on twenty pre-operative postero-anterior radiographs of Adolescent Idiopathic Scoliosis patients with both a standard protractor and using an Apple iPhone. Five of the observers repeated the measurements at least a week after the original measurements. Results: The mean absolute difference between pairs of iPhone/protractor measurements was 2.1°, with a small (1°) bias toward lower Cobb angles with the iPhone. 95% confidence intervals for intra-observer variability were ±3.3° for the protractor and ±3.9° for the iPhone. 95% confidence intervals for inter-observer variability were ±8.3° for the iPhone and ±7.1° for the protractor. Both of these confidence intervals were within the range of previously published Cobb measurement studies. Conclusions: We conclude that the iPhone is an equivalent Cobb measurement tool to the manual protractor, and measurement times are about 15% less. The widespread availability of inclinometer-equipped mobile phones and the ability to store measurements in later versions of the angle measurement software may make these new technologies attractive for clinical measurement applications.

Evaluation of the iPhone with an acrylic sleeve versus the Scoliometer for rib hump measurement in scoliosis

Background. Vertebral rotation found in structural scoliosis contributes to trunkal asymmetry which is commonly measured with a simple Scoliometer device on a patient's thorax in the forward flexed position. The new generation of mobile 'smartphones' have an integrated accelerometer, making accurate angle measurement possible, which provides a potentially useful clinical tool for assessing rib hump deformity. This study aimed to compare rib hump angle measurements performed using a Smartphone and traditional Scoliometer on a set of plaster torsos representing the range of torsional deformities seen in clinical practice. Methods. Nine observers measured the rib hump found on eight plaster torsos moulded from scoliosis patients with both a Scoliometer and an Apple iPhone on separate occasions. Each observer repeated the measurements at least a week after the original measurements, and were blinded to previous results. Intra-observer reliability and inter-observer reliability were analysed using the method of Bland and Altman and 95% confidence intervals were calculated. The Intra-Class Correlation Coefficients (ICC) were calculated for repeated measurements of each of the eight plaster torso moulds by the nine observers. Results. Mean absolute difference between pairs of iPhone/Scoliometer measurements was 2.1 degrees, with a small (1 degrees) bias toward higher rib hump angles with the iPhone. 95% confidence intervals for intra-observer variability were +/- 1.8 degrees (Scoliometer) and +/- 3.2 degrees (iPhone). 95% confidence intervals for inter-observer variability were +/- 4.9 degrees (iPhone) and +/- 3.8 degrees (Scoliometer). The measurement errors and confidence intervals found were similar to or better than the range of previously published thoracic rib hump measurement studies. Conclusions. The iPhone is a clinically equivalent rib hump measurement tool to the Scoliometer in spinal deformity patients. The novel use of plaster torsos as rib hump models avoids the variables of patient fatigue and discomfort, inconsistent positioning and deformity progression using human subjects in a single or multiple measurement sessions.